We're all coded with our past experiences. Sometimes that coding leads us in the right direction, but often it leads us in the wrong direction. How your life's experience, or your Chi Code, affects you is an individual thing. The concept of "Chi" comes from Chinese philosophy and means "life force". It is the life-giving, vital energy that unites body, mind and spirit and animates the body internally. This book is part memoir and part self-help book. It's here to guide you through your own journey by allowing you to see how I've healed through mine. For you to get something out of it, you have to exert some effort. Don't just sit back and read it, put these principles into practice in your life. At the end of every chapter, you'll find questions that will help you relate what you've just read to what you're personally experiencing. Write down your answers to the questions, even though I know it's easy to just gloss over them. These moments of reflection on your own reality will be valuable and will empower you to make the changes to your code necessary to realize your goals and create the life you envision for yourself. Your life is completely unique from mine, but we're the same in that we all have baggage from our past that we must deal with in the present if we want to create a different future. Reading this book, and more importantly relating it to yourself, is a positive step in the direction of bringing your past into the present. The hard truth is that you're carrying it with you either way. How you carry your experiences with you is a determining factor in whether you will live a broken and painful existence or a happy and fulfilled life. You deserve to be happy. You deserve to feel whole. You deserve to unlock your Chi Code and create the life that you've dreamed of.

A practical guide to data mining using SQL and Excel Data Analysis Using SQL and Excel, 2nd Edition shows you how to leverage the two most popular tools for data query and analysis—SQL and Excel—to perform sophisticated data analysis without the need for complex and expensive data mining tools. Written by a leading expert on business data mining, this book shows you how to extract useful business information from relational databases. You'll learn the fundamental techniques before moving into the "where" and "why" of each analysis, and then learn how to design and perform these analyses using SQL and Excel. Examples include SQL and Excel code, and the appendix shows how non-standard constructs are implemented in other major databases, including Oracle and IBM DB2/UDB. The companion website includes datasets and Excel spreadsheets, and the book provides hints, warnings, and technical asides to help you every step of the way. Data Analysis Using SQL and Excel, 2nd Edition shows you how to perform a wide range of sophisticated analyses using these simple tools, sparing you the significant expense of proprietary data mining tools like SAS. Understand core analytic techniques that work with SQL and Excel Ensure your analytic approach gets you the results you need Design and perform your analysis using SQL and Excel Data Analysis Using SQL and Excel, 2nd Edition shows you how to best use the tools you already know to achieve expert results.

Drawing on examples from across the social and behavioral sciences, Statistics With R: Solving Problems Using Real-World Data introduces foundational statistics concepts with beginner-friendly R programming in an exploration of the world’s tricky problems faced by the "R Team" characters.

THE JOSSEY-BASS READER ON Contemporary Issues in Adult Education With contributions from leading experts in the field, The Jossey-Bass Reader on Contemporary Issues in Adult Education collects in one volume the best previously published literature on the issues and trends affecting adult education today. The volume includes influential pieces from foundational authors in the profession such as Eduard C. Lindeman, Alain Locke, and Paulo Freire, as well as current work from authors around the world, including Laura L. Bierema, John M. Dirkx, Cecilia Amaluisa Fiallos, Peter Jarvis, Michael Newman, and Shirley Walters. In five sections, the book's thirty chapters delve into a wide range of compelling topics including: social justice, democracy, and activism diversity and marginalization human resource development lifelong learning ethical issues the meaning and role of emotions globalization and non-Western perspectives the role of mass media, popular culture, and "social learning" technology health, welfare, and environment Each piece is framed within its larger context by the editors, and each section is accompanied by helpful reflection and discussion questions.

Statistics is the activity of inferring results about a population given a sample. Historically, statistics books assume an underlying distribution to the data (typically, the normal distribution) and derive results under that assumption. Unfortunately, in real life, one cannot normally be sure of the underlying distribution. For that reason, this book presents a distribution-independent approach to statistics based on a simple computational counting idea called resampling. This book explains the basic concepts of resampling, then systematically presents the standard statistical measures along with programs (in the language Python) to calculate them using resampling, and finally illustrates the use of the measures and programs in a case study. The text uses junior high school algebra and many examples to explain the concepts. Th e ideal reader has mastered at least elementary mathematics, likes to think procedurally, and is comfortable with computers. Table of Contents: The Basic Idea / Pragmatic Considerations when Using Resampling / Terminology / The Essential Stats / Case Study: New Mexico's 2004 Presidential Ballots / References / Bias Corrected Confidence Intervals / Appendix B

'Data Analysis Using SQL and Excel' shows business managers and data analysts how to use the relatively simple tools of SQL and Excel to extract useful business information from relational databases.

A “how to” guide for applying statistical methods to biomarker data analysis Presenting a solid foundation for the statistical methods that are used to analyze biomarker data, Analysis of Biomarker Data: A Practical Guide features preferred techniques for biomarker validation. The authors provide descriptions of select elementary statistical methods that are traditionally used to analyze biomarker data with a focus on the proper application of each method, including necessary assumptions, software recommendations, and proper interpretation of computer output. In addition, the book discusses frequently encountered challenges in analyzing biomarker data and how to deal with them, methods for the quality assessment of biomarkers, and biomarker study designs. Covering a broad range of statistical methods that have been used to analyze biomarker data in published research studies, Analysis of Biomarker Data: A Practical Guide also features: A greater emphasis on the application of methods as opposed to the underlying statistical and mathematical theory The use of SAS®, R, and other software throughout to illustrate the presented calculations for each example Numerous exercises based on real-world data as well as solutions to the problems to aid in reader comprehension The principles of good research study design and the methods for assessing the quality of a newly proposed biomarker A companion website that includes a software appendix with multiple types of software and complete data sets from the book’s examples Analysis of Biomarker Data: A Practical Guide is an ideal upper-undergraduate and graduate-level textbook for courses in the biological or environmental sciences. An excellent reference for statisticians who routinely analyze and interpret biomarker data, the book is also useful for researchers who wish to perform their own analyses of biomarker data, such as toxicologists, pharmacologists, epidemiologists, environmental and clinical laboratory scientists, and other professionals in the health and environmental sciences.